Across our client work and reinforced during our recent AI roundtable with AWS, one truth stands out: Insurers seeing the fastest ROI from AI aren’t running multi-year transformation programmes. They’re starting small. Proving value quickly. Scaling what works.
This approach aligns perfectly with the operational realities of the insurance sector, where legacy systems, regulatory pressures and cross-team dependencies can slow down any large programme.
This article breaks down why starting small with AI is the winning strategy for insurance carriers, MGAs, and assistance providers and which workflows offer the quickest, safest path to measured value.
Big AI transformations are slow. Small AI projects deliver fast.
Enterprise-wide AI initiatives often stall because they require:
- major IT and core-system integration
- large budgets and governance cycles
- multi-department alignment
- long lead times before value is visible
But insurers adopting AI successfully today do the opposite:
- Start with one workflow
- Deliver value in weeks, not years
- Keep governance lightweight
- Scale only after success is proven
This reduces risk, accelerates adoption, and builds trust across underwriting, claims and operations.
Why this “Start Small” model works in insurance
✔ AI pilots don’t require perfect data
A simple, representative dataset is enough to test models, automation and enrichment.
✔ No dependency on legacy system replacement
Modern AI workflows integrate around existing systems using APIs, IDP, and agent-based orchestration.
✔ Teams see value quickly
Underwriters and claims handlers adopt AI when they see practical benefits — not theoretical ones.
✔ Governance is easier
Smaller pilots trigger less internal friction and can often be approved within weeks.
✔ ROI is demonstrated early
Measurable improvements in speed, accuracy or capacity secure sponsorship for further investment.
The best starting points for AI in insurance
From Firemind’s roundtable discussions and client implementations, insurers repeatedly succeed with AI in these high-value workflows:
- Claims triage & medical case summarisation: AI structures clinical notes, travel assistance cases or loss descriptions instantly.
- Travel & medical assistance scoring: Using AI to extract medical details, hospital quality, expected length of stay and potential cost exposure.
- Automated underwriting memos: Turning lengthy submissions into structured underwriter-ready summaries.
- Low-complexity claims automation: Luggage claims, simple cancellations and other low-value processes move toward straight-through processing.
- Document intelligence for high-volume workflows: Summarisation, entity extraction, comparison, consistency checks and enrichment.
These are safe, governed, low-risk ways to realise immediate AI benefits.
Joint Funding: The easiest way to start an insurance AI project
One of the biggest barriers insurers face is budget for early AI experimentation.
Firemind, AWS and NVIDIA are solving this by offering up to $100,000 in co-funding for eligible AI pilots.
This funding supports:
- AI for claims automation
- underwriting workflow automation
- agent-based orchestration
- IDP and document intelligence
- assistance risk scoring
- operational optimisation
It’s one of the simplest paths to de-risk adoption and accelerate delivery.
The path forward: start small, scale confidently
The insurers moving fastest in AI aren’t the ones with the biggest programmes, they’re the ones who:
- pick one workflow
- secure representative data
- define a measurable outcome
- prove value fast
- From there, scaling becomes a repeatable pattern.
If your team is exploring how to begin with AI in underwriting, claims or assistance, Firemind can help you scope, build and deploy a pilot, with optional co-funding support. Reach out to us today to kickstart your project!
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